Radiomics signature based on robust features derived from diffusion data for differentiation between benign and malignant solitary pulmonary lesions.

ABSTRACT:

Background

Classifying and characterizing pulmonary lesions are critical for clinical decision-making process to identify optimal therapeutic strategies. The purpose of this study was to develop and validate a radiomics nomogram for distinguishing between benign and malignant pulmonary lesions based on robust features derived from diffusion images.

Material and methods

The study was conducted in two phases. In the first phase, we prospectively collected 30 patients with pulmonary nodule/mass who underwent twice EPI-DWI scans. The robustness of features between the two scans was evaluated using the concordance correlation coefficient (CCC) and dynamic range (DR). In the second phase, 139 patients who underwent pulmonary DWI were randomly divided into training and test sets in

SUBMITTER: Zhou J 

PROVIDER: S-EPMC10802010 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature